How to effectively use neural networks in marketing

[tmonower957]

We tell you how to use the capabilities of neural networks to increase the effectiveness of advertising campaigns.

Advanced Advertising Options
Using neural network algorithms for photo recognition, you can expand your audience and increase the effectiveness of targeted advertising. The capabilities of neural networks in facial recognition are growing every year, so it can already determine gender, age, distinctive features such as beard, glasses, hair color, and emotions. In addition, the neural network identifies people with bad habits, certain hobbies, and those who prefer specific brands.

Using neural network tools, you can find a new audience with an accuracy of up to 90%, which would be impossible to identify using manual settings. You can also detail and personalize advertising for argentina consumer email list each segment of the target audience - neural networks analyze user behavior on a website or in an application, identifying their needs and preferences, on the basis of which they form relevant offers of goods or services.

Quick content creation
The human brain perceives visual information better than text, so advertising cannot do without accompanying media materials. Previously, images and videos were created and processed manually by individual employees. This took a lot of time and required a separate budget line, but now this same work is done by artificial intelligence.

An example of an image generated by the Kandinsky 2.0 neural network

So far, neural networks do not create original and unique content, but only generate materials from ready-made reference works, posted in the public domain and uploaded to the network during training. However, this does not reduce the value of the design created by machine algorithms, since neural networks are capable of producing high-quality content in a short time. To get an image, it is enough to write a text description of the desired result and the neural network will offer its options. Some of the popular platforms are Midjourney and Kandinsky 2.0, developed on the basis of the DALL-E model.

Neural networks speed up the process of creating not only visual but also text content many times over — for example, many platforms can generate descriptions of product cards, posts for social networks, press releases, short information articles and even advertisements. Popular services include: CopyMonkey, ChatGPT and Anyword. Most services have limited free versions, extended paid packages or a subscription.